Do-It-Yourself (DIY) online: Why making matters on Pinterest

The Do-It-Yourself (DIY) community is currently one of the largest creative content communities on Pinterest (Hall et al., 2018), a social networking service (SNS) that encourages users to both share information about creative processes and attempt projects in real life (IRL). Pinterest users share ongoing projects by creating Project “Pins”, which consist of images, videos, and text descriptions of creative content. And yet, while several studies have investigated user behavior in relation to everyday ideation and creativity on the site (Linder et al., 2014, Hu et al., 2018, Mull and Lee, 2014), little is known about the characteristics that lead users to prefer some DIY projects over others. Thus, this dissertation introduces the Pinterest-DIY data set, which consists of text data mined from 500 DIY project "Pins" on Pinterest. Using a custom sampling approach, a taxonomy of DIY characteristics related to each Pin’s project type, function, materials, and complexity was created during an initial study. To measure user preferences on the site, a sentiment analysis on user comments for each DIY project Pin was performed. This dissertation introduces the data set and presents two use cases for the internet research community using both exploratory and confirmatory statistical methods. This dissertation argues that the Pinterest-DIY data set will provide further opportunities to examine what is happening within DIY communities on Pinterest.